Specification points

AQA GCSE Statistics 8382

83 points in 6 topics, with AQA's codes and titles.

Codes and titles are read by a script from AQA's published specification and have not been checked by a person. What each point covers is in the specification itself: AQA’s specification.

3.1 Section A: planning a statistical investigation

3.1.1 A1: testing a hypothesis with data
3.1.2 A2: constraints on designing an investigation
3.1.3 A3: strategies for problems during an enquiry

3.2 Section B: collecting data

3.2.1 B1a: types of data
3.2.2 B1b: grouping data into categories and class intervals
3.2.3 B1c: explanatory and response variables
3.2.4 B2a: primary and secondary data
3.2.5 B2b: sources of data
3.2.6 B2c: reliability and validity of data
3.2.7 B2d: bias and minimising data distortion
3.2.8 B3a: population, sampling frame and sample
3.2.9 B3b: meanings of population in context
3.2.10 B3c: judgement and opportunity sampling
3.2.11 B3d: random, systematic and quota sampling
3.2.12 B3e: simple random samples and random selection
3.2.13 B3f: stratification before sampling
3.2.14 B4: planning data collection, questions and interviews
3.2.15 B5a: problems with collected data
3.2.16 B5b: cleaning data
3.2.17 B5c: extraneous variables and control groups

3.3 Section C: representing data

3.3.1 C1a: representing data pictorially
3.3.2 C1b: interpreting and comparing pictorial displays
3.3.3 C2: representing data graphically
3.3.4 C3a: choosing and producing an accurate visualisation
3.3.5 C3b: misleading graphs and misrepresentation
3.3.6 C4a: comparing data presented in different formats
3.3.7 C4b: choosing a form of representation

3.4 Section D: calculating statistical measures

3.4.1 D1a: averages for discrete and grouped data
3.4.2 D1b: choosing an appropriate average
3.4.3 D2: skewness
3.4.4 D3a: measures of spread
3.4.5 D3b: identifying outliers
3.4.6 D4: trends and moving averages
3.4.7 D5: lines of best fit and regression lines
3.4.8 D6: Spearman’s rank correlation coefficient
3.4.9 D7: estimating probabilities from data

3.5 Section E: interpreting and evaluating results

3.5.1 E1a: comparing probabilities on a scale
3.5.2 E1b: expected frequency
3.5.3 E1c: relative and absolute risk
3.5.4 E2a: experimental data against theoretical predictions
3.5.5 E2b: experimental probability and the number of trials
3.5.6 E2c: diagrams for combined outcomes
3.5.7 E3a: comparing data sets by central tendency
3.5.8 E3b: comparing data sets by spread
3.5.9 E3c: comparing samples with each other and populations
3.5.10 E3d: interpreting data in tables
3.5.11 E4a: notation for independent events
3.5.12 E4b: notation for conditional probability
3.5.13 E5a: interpreting skewness
3.5.14 E5b: commenting on outliers
3.5.15 E6: seasonal and cyclic trends
3.5.16 E7a: rates of change over time in graphs
3.5.17 E7b: calculating rates of change from tables
3.5.18 E7c: index numbers
3.5.19 E8a: vocabulary of correlation
3.5.20 E8b: strength of correlation
3.5.21 E8c: correlation and causation
3.5.22 E9a: interpreting Spearman’s rank correlation
3.5.23 E9b: interpreting Pearson’s product moment correlation
3.5.24 E9c: Spearman’s and Pearson’s coefficients compared
3.5.25 E10a: experimental and theoretical values and bias
3.5.26 E10b: the binomial distribution
3.5.27 E11a: the Normal distribution
3.5.28 E11b: standard deviations in a Normal distribution
3.5.29 E11c: action and warning lines in quality assurance
3.5.30 E11d: standardising data
3.5.31 E12a: estimating population characteristics from summaries
3.5.32 E12b: estimating a population mean from samples
3.5.33 E12c: predicting population proportions from samples
3.5.34 E12d: the Petersen capture–recapture method
3.5.35 E13a: sample size and reliability
3.5.36 E13b: the distribution of sample means

3.6 Statistical Enquiry Cycle (SEC)

3.6.1 Initial planning
3.6.2 Data collection
3.6.3 Data processing and presentation
3.6.4 Interpretation of results
3.6.5 Evaluation and review